Accurate early warning of rainfall-induced landslides poses a critical challenge in geological disaster risk management. Conventional deterministic rainfall threshold models often overlook the heterogeneity of regional geological conditions, while landslide susceptibility assessment is plagued by uncertainties in selecting non-landslide samples. To address these issues, this paper took Zhushan County in Hubei Province as the study area, and the semi-supervised random forest (SRF) model was adopted to conduct landslide susceptibility assessment. The critical rainfall (Effective Rainfall-Duration, EE-D) threshold curves were constructed based on the antecedent effective rainfall (EE) and rainfall duration (D). Furthermore, EE-D threshold curves with different geological condition characteristics were established and analyzed according to the thickness, slope, and area of the landslides, respectively. By coupling the landslide susceptibility results with a classified multi-level rainfall threshold model, a spatiotemporally refined regional framework for tiered landslide early warning was developed. The results show that the SRF model solves the problem of non-landslide sample selection error in traditional supervised learning. The Area Under Curve (AUC) value reaches 0.91, which is better than the analytic hierarchy process, logistic regression, etc. Moreover, the models of landslide susceptibility and EE-D threshold can effectively achieve the hierarchical early warning of rainfall-induced landslide hazards.

Groundwater is an important water source in China, yet its quality is increasingly threatened by industrial activities, including petroleum exploration. This study assessed seasonal hydrochemical characteristics, groundwater quality, and human health risks of shallow groundwater in the central Jianghan Plain, with emphasis on potential influences of petroleum-related activities. Groundwater samples collected during dry and wet seasons were analyzed for hydrochemical parameters, classified by hydrochemical facies, and evaluated using the water quality index (WQI), non-carcinogenic health risk assessment, and spatial distribution analysis. Groundwater was generally weakly alkaline and mainly hard to extremely hard, with HCO₃–Ca·Mg as the dominant hydrochemical facies and some samples shifting toward mixed HCO₃–Cl–Ca·Mg types. Most parameters had higher mean concentrations in the dry season, indicating wet-season dilution. Rock weathering dominated groundwater chemistry, whereas evaporation had limited influence. Elevated Cl⁻ suggested possible effects of petroleum-related activities. Overall groundwater quality was poor, with mean WQI values of 394.23 and 292.50 in the dry and wet seasons, respectively. Children showed greater vulnerability than adults, and Fe and As were the main contributors to non-carcinogenic risk. WQI and health-risk hotspots were concentrated near Zhouji and adjacent petroleum exploration areas, indicating the need for long-term monitoring and risk management.